Fast oscillations >40 Hz localize the epileptogenic zone: An electrical source imaging study using high-density electroencephalography

Scalp high-frequency oscillation spatial distribution is consistent over consecutive nights, while rates vary with antiseizure medication changes

OBJECTIVE

This study aimed to investigate two key aspects of scalp high-frequency oscillations (HFOs) in pediatric focal lesional epilepsy: (1) the stability of scalp HFO spatial distribution across consecutive nights, and (2) the variation in scalp HFO rates in response to changes in antiseizure medication (ASM).

METHODS

We analyzed 81 whole-night scalp electroencephalography (EEG) recordings from 20 children with focal lesional epilepsy. We used a previously validated automated HFO detector to assess scalp HFO rates (80-250 Hz) during non-rapid eye movement (NREM) sleep. The spatial distribution of HFO rates across consecutive nights was evaluated using Hamming similarity, and changes in ASM were classified as increased, decreased, or stable.

RESULTS

For each patient, we analyzed 3 ± 1 whole-night scalp EEG recordings, with a mean duration of 650 ± 215 min per recording. The distribution of HFO remained stable across consecutive nights, with a Hamming similarity of 88% ± 6%. Four patients had at least one ASM dosage decrease, nine patients had both ASM dosage decreases and increases, two patients had only ASM dosage increases, and five patients had no changes in ASM during the study period. A decrease in ASM dosage was associated with increased HFO rates (from .16 ± .32 to .22 ± .36 HFO/min; p = .03), whereas an increase in ASM dosage led to decreased HFO rates (from .32 ± .54 HFO/min to .22 ± .38 HFO/min; p = .005) when comparing the last night to the first.

SIGNIFICANCE

The spatial distribution of scalp HFOs remained consistent across multiple nights, whereas fluctuations in HFO rates correlated with changes in ASM dosage. These findings suggest that scalp HFOs may not only help identify epileptogenic brain tissue but also monitor treatment response.

Low-density scalp electrical source imaging of the ictal onset zone network using source coherence maps

Introduction

This study investigated low-density scalp electrical source imaging of the ictal onset zone and interictal spike ripple high-frequency oscillation networks using source coherence maps in the pediatric epilepsy surgical workup. Intracranial monitoring, the gold standard for determining epileptogenic zones, has limited spatial sampling. Source coherence analysis presents a promising new non-invasive technique.

Methods

This was a retrospective review of 12 patients who underwent focal resections. Source coherence maps were generated using standardized low-resolution electromagnetic tomography and concordance to resection margins was assessed, noting outcomes at 3 years post-surgery.

Results

Ictal source coherence maps were performed in 7/12 patients. Six of seven included the surgical resection. Five of seven cases were seizure free post-resection. Interictal spike ripple electrical source imaging and interictal spike ripple high-frequency oscillation networks using source coherence maps were performed for three cases, with two of three included in the resection and all three were seizure free.

Discussion

These findings may provide proof of principle supporting low-density scalp electrical source imaging of the ictal onset zone and spike ripple network using source coherence maps. This promising method is complementary to ictal and interictal electrical source imaging in the pediatric epilepsy surgical workup, guiding electrode placement for intracranial monitoring to identify the epileptogenic zone.

Human brain imaging with high-density electroencephalography: Techniques and applications

Electroencephalography (EEG) is a technique for non-invasively measuring neuronal activity in the human brain using electrodes placed on the participant's scalp. With the advancement of digital technologies, EEG analysis has evolved over time from the qualitative analysis of amplitude and frequency modulations to a comprehensive analysis of the complex spatiotemporal characteristics of the recorded signals. EEG is now considered a powerful tool for measuring neural processes in the same time frame in which they happen (i.e. the subsecond range). However, it is commonly argued that EEG suffers from low spatial resolution, which makes it difficult to localize the generators of EEG activity accurately and reliably. Today, the availability of high-density EEG (hdEEG) systems, combined with methods for incorporating information on head anatomy and sophisticated source-localization algorithms, has transformed EEG into an important neuroimaging tool. hdEEG offers researchers and clinicians a rich and varied range of applications. It can be used not only for investigating neural correlates in motor and cognitive neuroscience experiments, but also for clinical diagnosis, particularly in the detection of epilepsy and the characterization of neural impairments in a wide range of neurological disorders. Notably, the integration of hdEEG systems with other physiological recordings, such as kinematic and/or electromyography data, might be especially beneficial to better understand the neuromuscular mechanisms associated with deconditioning in ageing and neuromotor disorders, by mapping the neurokinematic and neuromuscular connectivity patterns directly in the brain.

EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy

Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.

Use, experience and perspectives of high-density EEG among Italian epilepsy centers: a national survey

INTRODUCTION

High-density EEG (hdEEG) is a validated tool in presurgical evaluation of people with epilepsy. The aim of this national survey is to estimate diffusion and knowledge of hdEEG to develop a network among Italian epilepsy centers.

METHODS

A survey of 16 items (and 15 additional items) was distributed nationwide by email to all members of the Italian League Against Epilepsy and the Italian Society of Clinical Neurophysiology. The data obtained were analyzed using descriptive statistics.

RESULTS

A total of 104 respondents were collected from 85 centers, 82% from the Centre-North of Italy; 27% of the respondents had a hdEEG. The main applications were for epileptogenic focus characterization in the pre-surgical evaluation (35%), biomarker research (35%) and scientific activity (30%). The greatest obstacles to hdEEG were economic resources (35%), acquisition of dedicated personnel (30%) and finding expertise (17%). Dissemination was limited by difficulties in finding expertise and dedicated personnel (74%) more than buying devices (9%); 43% of the respondents have already published hdEEG data, and 91% of centers were available to participate in multicenter hdEEG studies, helping in both pre-processing and analysis. Eighty-nine percent of respondents would be interested in referring patients to centers with established experience for clinical and research purposes.

CONCLUSIONS

In Italy, hdEEG is mainly used in third-level epilepsy centers for research and clinical purposes. HdEEG diffusion is limited not only by costs but also by lack of trained personnel. Italian centers demonstrated a high interest in educational initiatives on hdEEG as well as in clinical and research collaborations.

Consistency of electrical source imaging in presurgical evaluation of epilepsy across different vigilance states

OBJECTIVE

The use of electrical source imaging (ESI) in assessing the source of interictal epileptic discharges (IEDs) is gaining increasing popularity in presurgical work-up of patients with drug-resistant focal epilepsy. While vigilance affects the ability to locate IEDs and identify the epileptogenic zone, we know little about its impact on ESI.

METHODS

We studied overnight high-density electroencephalography recordings in focal drug-resistant epilepsy. IEDs were marked visually in each vigilance state, and examined in the sensor and source space. ESIs were calculated and compared between all vigilance states and the clinical ground truth. Two conditions were considered within each vigilance state, an unequalized and an equalized number of IEDs.

RESULTS

The number, amplitude, and duration of IEDs were affected by the vigilance state, with N3 sleep presenting the highest number, amplitude, and duration for both conditions (P < 0.001), while signal-to-noise ratio only differed in the unequalized condition (P < 0.001). The vigilance state did not affect channel involvement (P > 0.05). ESI maps showed no differences in distance, quality, extent, or maxima distances compared to the clinical ground truth for both conditions (P > 0.05). Only when an absolute reference (wakefulness) was used, the channel involvement (P < 0.05) and ESI source extent (P < 0.01) were impacted during rapid-eye-movement (REM) sleep. Clustering of amplitude-sensitive and -insensitive ESI maps pointed to amplitude rather than the spatial profile as the driver (P < 0.05).

INTERPRETATION

IED ESI results are stable across vigilance states, including REM sleep, if controlled for amplitude and IED number. ESI is thus stable and invariant to the vigilance state.

Targeted density electrode placement achieves high concordance with traditional high-density EEG for electrical source imaging in epilepsy

OBJECTIVE

High-density (HD) electroencephalography (EEG) is increasingly used in presurgical epilepsy evaluation, but it is demanding in time and resources. To overcome these issues, we compared EEG source imaging (ESI) solutions with a targeted density and HD-EEG montage.

METHODS

HD-EEGs from patients undergoing presurgical evaluation were analyzed. A low-density recording was created by selecting the 25 electrodes of a standard montage from the 83 electrodes of the HD-EEG and adding 8-11 electrodes around the electrode with the highest amplitude interictal epileptiform discharges. The ESI solution from this "targeted" montage was compared to that from the HD-EEG using the distance between peak vertices, sublobar concordance and a qualitative similarity measure.

RESULTS

Fifty-eight foci of forty-three patients were included. The median distance between the peak vertices of the two montages was 13.2 mm, irrespective of focus' location. Tangential generators (n = 5/58) showed a higher distance than radial generators (p = 0.04). We found sublobar concordance in 54/58 of the foci (93%). Map similarity, assessed by an epileptologist, had a median score of 4/5.

CONCLUSIONS

ESI solutions obtained from a targeted density montage show high concordance with those calculated from HD-EEG.

SIGNIFICANCE

Requiring significantly fewer electrodes, targeted density EEG allows obtaining similar ESI solutions as traditional HD-EEG montage.

Rolling in the Deep: Surface EEG Seizures Viewed Through the Lens of Stereo EEG

Intracerebral Correlates of Scalp EEG Ictal Discharges Based on Simultaneous Stereo-EEG Recordings Ferrand M, Baumann C, Aron O, Vignal JP, Jonas J, Tyvaert L, Colnat-Coulbois S, Koessler L, Maillard L. Neurology . 2023 Mar 24:10.1212/WNL.0000000000207135 . doi:10.1212/WNL.0000000000207135 . Epub ahead of print. PMID: 36963841. Background and objectives: It remains unknown to what extent ictal scalp EEG can accurately predict the localization of the intra-cerebral seizure onset in pre-surgical evaluation of drug resistant epilepsies. In this study, we aimed to define homogeneous ictal scalp EEG profiles (based on their first ictal abnormality) and assess their localizing value using simultaneously recorded scalp EEG and Stereo-EEG. Methods: We retrospectively included consecutive patients with drug-resistant focal epilepsy who had simultaneous stereo-EEG and scalp EEG recordings of at least one seizure, in the epileptology unit in Nancy, France. We analyzed one seizure per patient and used hierarchical cluster analysis to group similar seizure profiles on scalp EEG and then performed a descriptive analysis of their intra-cerebral correlates. Results: We enrolled 129 patients in this study. The hierarchical cluster analysis showed six profiles on scalp EEG first modification. None was specific to a single intra-cerebral localization. The “normal EEG” and “blurred EEG” clusters (early muscle artifacts) comprised only five patients each and corresponded to no preferential intra-cerebral localization. The “temporal discharge” cluster (n = 46) was characterized by theta or delta discharges on ipsilateral anterior temporal scalp electrodes and corresponded to a preferential mesial temporal intra-cerebral localization. The “posterior discharge” cluster (n = 42) was characterized by posterior ipsilateral or contralateral rhythmic alpha discharges or slow waves on scalp and corresponded to a preferential temporal localization. However, this profile was the statistically most frequent scalp EEG correlate of occipital and parietal seizures. The “diffuse suppression” cluster (n = 9) was characterized by a bilateral and diffuse background activity suppression on scalp and corresponded to mesial, and particularly insulo-opercular, localization. Finally, the “frontal discharge” cluster (n = 22) was characterized by bilateral frontal rhythmic fast activity or pre-ictal spike on scalp and corresponded to preferential ventrodorsal frontal intra-cerebral localizations. Discussion: Hierarchical cluster analysis identified six seizure profiles regarding the first abnormality on scalp EEG. None of them was specific of a single intra-cerebral localization. Nevertheless, the strong relationships between the “temporal”, “frontal”, “diffuse suppression” and “posterior” profiles and intra-cerebral discharges localizations may contribute to hierarchize hypotheses derived from ictal scalp EEG analysis regarding intra-cerebral seizure onset.

Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas

BACKGROUND

Magnetoencephalography (MEG) is a widely used non-invasive tool to estimate brain activity with high temporal resolution. However, due to the ill-posed nature of the MEG source imaging (MSI) problem, the ability of MSI to identify accurately underlying brain sources along the cortical surface is still uncertain and requires validation.

METHOD

We validated the ability of MSI to estimate the background resting state activity of 45 healthy participants by comparing it to the intracranial EEG (iEEG) atlas (https://mni-open-ieegatlas.

RESEARCH

mcgill.ca/). First, we applied wavelet-based Maximum Entropy on the Mean (wMEM) as an MSI technique. Next, we converted MEG source maps into intracranial space by applying a forward model to the MEG-reconstructed source maps, and estimated virtual iEEG (ViEEG) potentials on each iEEG channel location; we finally quantitatively compared those with actual iEEG signals from the atlas for 38 regions of interest in the canonical frequency bands.

RESULTS

The MEG spectra were more accurately estimated in the lateral regions compared to the medial regions. The regions with higher amplitude in the ViEEG than in the iEEG were more accurately recovered. In the deep regions, MEG-estimated amplitudes were largely underestimated and the spectra were poorly recovered. Overall, our wMEM results were similar to those obtained with minimum norm or beamformer source localization. Moreover, the MEG largely overestimated oscillatory peaks in the alpha band, especially in the anterior and deep regions. This is possibly due to higher phase synchronization of alpha oscillations over extended regions, exceeding the spatial sensitivity of iEEG but detected by MEG. Importantly, we found that MEG-estimated spectra were more comparable to spectra from the iEEG atlas after the aperiodic components were removed.

CONCLUSION

This study identifies brain regions and frequencies for which MEG source analysis is likely to be reliable, a promising step towards resolving the uncertainty in recovering intracerebral activity from non-invasive MEG studies.

Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy

Since the discovery of the human electroencephalogram (EEG), neurophysiology techniques have become indispensable tools in our armamentarium to localize epileptic seizures. New signal analysis techniques and the prospects of artificial intelligence and big data will offer unprecedented opportunities to further advance the field in the near future, ultimately resulting in improved quality of life for many patients with drug-resistant epilepsy. This article summarizes selected presentations from Day 1 of the two-day symposium "Neurophysiology, Neuropsychology, Epilepsy, 2022: Hills We Have Climbed and the Hills Ahead". Day 1 was dedicated to highlighting and honoring the work of Dr. Jean Gotman, a pioneer in EEG, intracranial EEG, simultaneous EEG/ functional magnetic resonance imaging, and signal analysis of epilepsy. The program focused on two main research directions of Dr. Gotman, and was dedicated to "High-frequency oscillations, a new biomarker of epilepsy" and "Probing the epileptic focus from inside and outside". All talks were presented by colleagues and former trainees of Dr. Gotman. The extended summaries provide an overview of historical and current work in the neurophysiology of epilepsy with emphasis on novel EEG biomarkers of epilepsy and source imaging and concluded with an outlook on the future of epilepsy research, and what is needed to bring the field to the next level.

'High-Density-SleepCleaner': An open-source, semi-automatic artifact removal routine tailored to high-density sleep EEG

BACKGROUND

With up to 256 channels, high-density electroencephalography (hd-EEG) has become essential to the sleep research field. The vast amount of data resulting from this magnitude of channels in overnight EEG recordings complicates the removal of artifacts.

NEW METHOD

We present a new, semi-automatic artifact removal routine specifically designed for sleep hd-EEG recordings. By employing a graphical user interface (GUI), the user assesses epochs in regard to four sleep quality markers (SQMs). Based on their topography and underlying EEG signal, the user eventually removes artifactual values. To identify artifacts, the user is required to have basic knowledge of the typical (patho-)physiological EEG they are interested in, as well as artifactual EEG. The final output consists of a binary matrix (channels x epochs). Channels affected by artifacts can be restored in afflicted epochs using epoch-wise interpolation, a function included in the online repository.

RESULTS

The routine was applied in 54 overnight sleep hd-EEG recordings. The proportion of bad epochs highly depends on the number of channels required to be artifact-free. Between 95% and 100% of bad epochs could be restored using epoch-wise interpolation. We furthermore present a detailed examination of two extreme cases (with few and many artifacts). For both nights, the topography and cyclic pattern of delta power look as expected after artifact removal.

COMPARISON WITH EXISTING METHODS

Numerous artifact removal methods exist, yet their scope of application usually targets short wake EEG recordings. The proposed routine provides a transparent, practical, and efficient approach to identify artifacts in overnight sleep hd-EEG recordings.

CONCLUSION

This method reliably identifies artifacts simultaneously in all channels and epochs.

Focal epilepsy impacts rapid eye movement sleep microstructure

STUDY OBJECTIVES

Whereas there is plenty of evidence on the influence of epileptic activity on non-rapid eye movement (NREM) sleep macro- and micro-structure, data on the impact of epilepsy on rapid eye movement (REM) sleep remains sparse. Using high-density electroencephalography (HD-EEG), we assessed global and focal disturbances of sawtooth waves (STW) as cortically generated sleep oscillations of REM sleep in patients with focal epilepsy.

METHODS

Twenty-two patients with drug-resistant focal epilepsy (13 females; mean age, 32.6 ± 10.7 years; 12 temporal lobe epilepsy) and 12 healthy controls (3 females; 24.0 ± 3.2 years) underwent combined overnight HD-EEG and polysomnography. STW rate, duration, frequency, power, spatial extent, IED rates and sleep homeostatic properties were analyzed.

RESULTS

STW rate and duration were reduced in patients with focal epilepsy compared to healthy controls (rate: 0.64/min ± 0.46 vs. 1.12/min ± 0.41, p = .005, d = -0.98; duration: 3.60 s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = -1.01). Not surprisingly given the fronto-central maximum of STW, the reductions were driven by extratemporal lobe epilepsy patients (rate: 0.45/min ± 0.31 vs. 1.12/min ± 0.41, p = .0004, d = -1.35; duration: 3.49 s ± 0.92 vs. 4.57 ± 1.00, p = .017, d = -0.99) and were more pronounced in the first vs. the last sleep cycle (rate first cycle patients vs. controls: 0.60/min ± 0.49 vs. 1.10/min ± 0.55, p = .016, d = -0.90, rate last cycle patients vs. controls: 0.67/min ± 0.51 vs. 0.99/min ± 0.49, p = .11, d = -0.62; duration first cycle patients vs. controls: 3.60s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = -1.01, duration last cycle patients vs. controls: 3.66s ± 0.84 vs. 4.51 ± 1.26, p = .039, d = -0.80). There was no regional decrease of STWs in the region with the epileptic focus vs. the contralateral side (all p > .05).

CONCLUSION

Patients with focal epilepsy and in particular extratemporal lobe epilepsy show a global reduction of STW activity in REM sleep. This may suggest that epilepsy impacts cortically generated sleep oscillations even in REM sleep when epileptic activity is low.

Focal epilepsy disrupts spindle structure and function

Sleep spindles are the hallmark of N2 sleep and are attributed a key role in cognition. Little is known about the impact of epilepsy on sleep oscillations underlying sleep-related functions. This study assessed changes in the global spindle rate in patients with epilepsy, analysed the distribution of spindles in relation to the epileptic focus, and performed correlations with neurocognitive function. Twenty-one patients with drug-resistant focal epilepsy (12 females; mean age 32.6 ± 10.7 years [mean ± SD]) and 12 healthy controls (3 females; 24.5 ± 3.3 years) underwent combined whole-night high-density electroencephalography and polysomnography. Global spindle rates during N2 were lower in epilepsy patients compared to controls (mean = 5.78/min ± 0.72 vs. 6.49/min ± 0.71, p = 0.02, d =  − 0.70). Within epilepsy patients, spindle rates were lower in the region of the epileptic focus compared to the contralateral region (median = 4.77/min [range 2.53–6.18] vs. 5.26/min [2.53–6.56], p = 0.02, rank biserial correlation RC =  − 0.57). This decrease was driven by fast spindles (12–16 Hz) (1.50/min [0.62–4.08] vs. 1.65/min [0.51–4.28], p = 0.002, RC =  − 0.76). The focal reduction in spindles was negatively correlated with two scales of attention (r =  − 0.54, p = 0.01; r =  − 0.51, p = 0.025). Patients with focal epilepsy show a reduction in global and local spindle rates dependent on the region of the epileptic focus. This may play a role in impaired cognitive functioning. Future work will show if the local reduction in spindles can be used as potential marker of the epileptic focus.

Advanced neuroimaging techniques in epilepsy

PURPOSE OF REVIEW

We review significant advances in epilepsy imaging in recent years.

RECENT FINDINGS

Structural MRI at 7T with optimization of acquisition and postacquisition image processing increases the diagnostic yield but artefactual findings remain a challenge. MRI analysis from multiple sites indicates different atrophy patterns and white matter diffusion abnormalities in temporal lobe and generalized epilepsies, with greater abnormalities close to the presumed seizure source. Structural and functional connectivity relate to seizure spread and generalization; longitudinal studies are needed to clarify the causal relationship of these associations. Diffusion MRI may help predict surgical outcome and network abnormalities extending beyond the epileptogenic zone. Three-dimensional multimodal imaging can increase the precision of epilepsy surgery, improve seizure outcome and reduce complications. Language and memory fMRI are useful predictors of postoperative deficits, and lead to risk minimization. FDG PET is useful for clinical studies and specific ligands probe the pathophysiology of neurochemical fluxes and receptor abnormalities.

SUMMARY

Improved structural MRI increases detection of abnormalities that may underlie epilepsy. Diffusion, structural and functional MRI indicate the widespread associations of epilepsy syndromes. These can assist stratification of surgical outcome and minimize risk. PET has continued utility clinically and for research into the pathophysiology of epilepsies.

Are High Frequency Oscillations in Scalp EEG Related to Age?

BACKGROUND

High-frequency oscillations (HFOs) have received much attention in recent years, particularly in the clinical context. In addition to their application as a marker for pathological changes in patients with epilepsy, HFOs have also been brought into context with several physiological mechanisms. Furthermore, recent studies reported a relation between an increase of HFO rate and age in invasive EEG recordings. The present study aimed to investigate whether this relation can be replicated in scalp-EEG.

METHODS

We recorded high-density EEG from 11 epilepsy patients at rest as well as during motor performance. Manual detection of HFOs was performed by two independent raters following a standardized protocol. Patients were grouped by age into younger (<25 years) and older (>50 years) participants.

RESULTS

No significant difference of HFO-rates was found between groups [U = 10.5, p = 0.429, r = 0.3].

CONCLUSIONS

Lack of replicability of the age effect of HFOs may be due to the local propagation patterns of age-related HFOs occurring in deep structures. However, limitations such as small sample size, decreased signal-to-noise ratio as compared to invasive recordings, as well as HFO-mimicking artifacts must be considered.

Evaluation of a personalized functional near infra-red optical tomography workflow using maximum entropy on the mean

In the present study, we proposed and evaluated a workflow of personalized near infra-red optical tomography (NIROT) using functional near-infrared spectroscopy (fNIRS) for spatiotemporal imaging of cortical hemodynamic fluctuations. The proposed workflow from fNIRS data acquisition to local 3D reconstruction consists of: (a) the personalized optimal montage maximizing fNIRS channel sensitivity to a predefined targeted brain region; (b) the optimized fNIRS data acquisition involving installation of optodes and digitalization of their positions using a neuronavigation system; and (c) the 3D local reconstruction using maximum entropy on the mean (MEM) to accurately estimate the location and spatial extent of fNIRS hemodynamic fluctuations along the cortical surface. The workflow was evaluated on finger-tapping fNIRS data acquired from 10 healthy subjects for whom we estimated the reconstructed NIROT spatiotemporal images and compared with functional magnetic resonance imaging (fMRI) results from the same individuals. Using the fMRI activation maps as our reference, we quantitatively compared the performance of two NIROT approaches, the MEM framework and the conventional minimum norm estimation (MNE) method. Quantitative comparisons were performed at both single subject and group-level. Overall, our results suggested that MEM provided better spatial accuracy than MNE, while both methods offered similar temporal accuracy when reconstructing oxygenated (HbO) and deoxygenated hemoglobin (HbR) concentration changes evoked by finger-tapping. Our proposed complete workflow was made available in the brainstorm fNIRS processing plugin-NIRSTORM, thus providing the opportunity for other researchers to further apply it to other tasks and on larger populations.

Spontaneous modulations of high-frequency cortical activity

OBJECTIVE

We clarified the clinical and mechanistic significance of physiological modulations of high-frequency broadband cortical activity associated with spontaneous saccadic eye movements during a resting state.

METHODS

We studied 30 patients who underwent epilepsy surgery following extraoperative electrocorticography and electrooculography recordings. We determined whether high-gamma activity at 70-110 Hz preceding saccade onset would predict upcoming ocular behaviors. We assessed how accurately the model incorporating saccade-related high-gamma modulations would localize the primary visual cortex defined by electrical stimulation.

RESULTS

The dynamic atlas demonstrated transient high-gamma suppression in the striatal cortex before saccade onset and high-gamma augmentation subsequently involving the widespread posterior brain regions. More intense striatal high-gamma suppression predicted the upcoming saccade directed to the ipsilateral side and lasting longer in duration. The bagged-tree-ensemble model demonstrated that intense saccade-related high-gamma modulations localized the visual cortex with an accuracy of 95%.

CONCLUSIONS

We successfully animated the neural dynamics supporting saccadic suppression, a principal mechanism minimizing the perception of blurred vision during rapid eye movements. The primary visual cortex per se may prepare actively in advance for massive image motion expected during upcoming prolonged saccades.

SIGNIFICANCE

Measuring saccade-related electrocorticographic signals may help localize the visual cortex and avoid misperceiving physiological high-frequency activity as epileptogenic.

Noninvasive Mapping of Ripple Onset Predicts Outcome in Epilepsy Surgery

OBJECTIVE

Intracranial electroencephalographic (icEEG) studies show that interictal ripples propagate across the brain of children with medically refractory epilepsy (MRE), and the onset of this propagation (ripple onset zone [ROZ]) estimates the epileptogenic zone. It is still unknown whether we can map this propagation noninvasively. The goal of this study is to map ripples (ripple zone [RZ]) and their propagation onset (ROZ) using high-density EEG (HD-EEG) and magnetoencephalography (MEG), and to estimate their prognostic value in pediatric epilepsy surgery.

METHODS

We retrospectively analyzed simultaneous HD-EEG and MEG data from 28 children with MRE who underwent icEEG and epilepsy surgery. Using electric and magnetic source imaging, we estimated virtual sensors (VSs) at brain locations that matched the icEEG implantation. We detected ripples on VSs, defined the virtual RZ and virtual ROZ, and estimated their distance from icEEG. We assessed the predictive value of resecting virtual RZ and virtual ROZ for postsurgical outcome. Interictal spike localization on HD-EEG and MEG was also performed and compared with ripples.

RESULTS

We mapped ripple propagation in all patients with HD-EEG and in 27 (96%) patients with MEG. The distance from icEEG did not differ between HD-EEG and MEG when mapping the RZ (26-27mm, p = 0.6) or ROZ (22-24mm, p = 0.4). Resecting the virtual ROZ, but not virtual RZ or the sources of spikes, was associated with good outcome for HD-EEG (p = 0.016) and MEG (p = 0.047).

INTERPRETATION

HD-EEG and MEG can map interictal ripples and their propagation onset (virtual ROZ). Noninvasively mapping the ripple onset may augment epilepsy surgery planning and improve surgical outcome of children with MRE. ANN NEUROL 2021;89:911-925.